test_aug15.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Untitled1.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNL2SGgIATJnD5dQkg5fAm+",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/lkkmills/gee/blob/main/test_aug15.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VixJkdUJDQcW",
        "outputId": "6326b5b8-9686-4a6d-e541-5699a6d5c1b1"
      },
      "source": [
        "import ee\n",
        "\n",
        "# Trigger the authentication flow.\n",
        "ee.Authenticate()\n",
        "\n",
        "# Initialize the library.\n",
        "ee.Initialize()"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "To authorize access needed by Earth Engine, open the following URL in a web browser and follow the instructions. If the web browser does not start automatically, please manually browse the URL below.\n",
            "\n",
            "    https://accounts.google.com/o/oauth2/auth?client_id=517222506229-vsmmajv00ul0bs7p89v5m89qs8eb9359.apps.googleusercontent.com&scope=https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fearthengine+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdevstorage.full_control&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&response_type=code&code_challenge=4KQ4upP0ru4-9szLgyLbummVtsOa11zrrqaHroqDGP4&code_challenge_method=S256\n",
            "\n",
            "The authorization workflow will generate a code, which you should paste in the box below. \n",
            "Enter verification code: 4/1AX4XfWhHvfyhQ9B38dy8t4blbW3dM1Py_4UGFTSFo-yyyXHr3WrLaiWSvb4\n",
            "\n",
            "Successfully saved authorization token.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sJuLek51DW0Q",
        "outputId": "818d7807-9126-4040-94ac-cb7b837be6b0"
      },
      "source": [
        "# Load a Landsat image.\n",
        "img = ee.Image('LANDSAT/LT05/C01/T1_SR/LT05_034033_20000913')\n",
        "\n",
        "# Print image object WITHOUT call to getInfo(); prints serialized request instructions.\n",
        "print(img)\n",
        "\n",
        "# Print image object WITH call to getInfo(); prints image metadata.\n",
        "print(img.getInfo())"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ee.Image({\n",
            "  \"functionInvocationValue\": {\n",
            "    \"functionName\": \"Image.load\",\n",
            "    \"arguments\": {\n",
            "      \"id\": {\n",
            "        \"constantValue\": \"LANDSAT/LT05/C01/T1_SR/LT05_034033_20000913\"\n",
            "      }\n",
            "    }\n",
            "  }\n",
            "})\n",
            "{'type': 'Image', 'bands': [{'id': 'B1', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': -32768, 'max': 32767}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'B2', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': -32768, 'max': 32767}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'B3', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': -32768, 'max': 32767}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'B4', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': -32768, 'max': 32767}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'B5', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': -32768, 'max': 32767}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'B6', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': -32768, 'max': 32767}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'B7', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': -32768, 'max': 32767}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'sr_atmos_opacity', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': -32768, 'max': 32767}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'sr_cloud_qa', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': 0, 'max': 255}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'pixel_qa', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': 0, 'max': 65535}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}, {'id': 'radsat_qa', 'data_type': {'type': 'PixelType', 'precision': 'int', 'min': 0, 'max': 255}, 'dimensions': [7961, 7301], 'crs': 'EPSG:32613', 'crs_transform': [30, 0, 270285, 0, -30, 4414815]}], 'id': 'LANDSAT/LT05/C01/T1_SR/LT05_034033_20000913', 'version': 1538944486718967, 'properties': {'IMAGE_QUALITY': 9, 'SATELLITE': 'LANDSAT_5', 'SOLAR_AZIMUTH_ANGLE': 141.401031, 'CLOUD_COVER': 0, 'WRS_PATH': 34, 'EARTH_SUN_DISTANCE': 1.005947, 'system:time_start': 968865725989, 'LANDSAT_ID': 'LT05_L1TP_034033_20000913_20160918_01_T1', 'SENSING_TIME': '2000-09-13T17:22:05.9890880Z', 'ESPA_VERSION': '2_19_0c', 'SOLAR_ZENITH_ANGLE': 41.934059, 'system:footprint': {'type': 'LinearRing', 'coordinates': [[-107.02869086291923, 39.84432363800019], [-107.07980980087045, 39.85126661965529], [-107.08652717633666, 39.849697643108755], [-107.0897758455212, 39.8405819578208], [-107.11182940314823, 39.7707179631659], [-107.21879155445666, 39.413849310454374], [-107.37259194928556, 38.891052103694385], [-107.52433643751696, 38.368081812423796], [-107.55395385669085, 38.263097139745526], [-107.56063282665062, 38.23679490602129], [-107.55934893818782, 38.23317297774577], [-105.49311751312952, 37.930606804132815], [-105.48965894759056, 37.939600449971515], [-105.4779323992155, 37.97426299040739], [-105.4665343056877, 38.00837900396258], [-105.29373593893524, 38.543204771752215], [-105.00027724293751, 39.443187322446825], [-104.96794099898516, 39.54191304485849], [-107.02869086291923, 39.84432363800019]]}, 'WRS_ROW': 33, 'GEOMETRIC_RMSE_MODEL_Y': 3.358, 'LEVEL1_PRODUCTION_DATE': 1474209899000, 'CLOUD_COVER_LAND': 0, 'GEOMETRIC_RMSE_MODEL_X': 2.493, 'system:asset_size': 365532987, 'GEOMETRIC_RMSE_MODEL': 4.182, 'SR_APP_VERSION': 'LEDAPS_3.2.0', 'PIXEL_QA_VERSION': 'generate_pixel_qa_1.5.0', 'system:index': 'LT05_034033_20000913'}}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BBOxVDICDo5s"
      },
      "source": [
        "import folium\n",
        "\n",
        "\n",
        "def add_ee_layer(self, ee_image_object, vis_params, name):\n",
        "  map_id_dict = ee.Image(ee_image_object).getMapId(vis_params)\n",
        "  folium.raster_layers.TileLayer(\n",
        "      tiles=map_id_dict['tile_fetcher'].url_format,\n",
        "      attr='Map Data &copy; <a href=\"https://earthengine.google.com/\">Google Earth Engine</a>',\n",
        "      name=name,\n",
        "      overlay=True,\n",
        "      control=True\n",
        "  ).add_to(self)\n",
        "\n",
        "folium.Map.add_ee_layer = add_ee_layer"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AsE840CAJq2r",
        "outputId": "fd44dbd1-37e5-46fe-dd57-d3e26813a495"
      },
      "source": [
        "img = ee.ImageCollection('NOAA/VIIRS/DNB/MONTHLY_V1/VCMCFG')\n",
        "print(img)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ee.ImageCollection({\n",
            "  \"functionInvocationValue\": {\n",
            "    \"functionName\": \"ImageCollection.load\",\n",
            "    \"arguments\": {\n",
            "      \"id\": {\n",
            "        \"constantValue\": \"NOAA/VIIRS/DNB/MONTHLY_V1/VCMCFG\"\n",
            "      }\n",
            "    }\n",
            "  }\n",
            "})\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cdqQzvmHNBBn",
        "outputId": "9961abc8-31fd-4bf6-c23c-a3ee02e9647a"
      },
      "source": [
        "nighttime_img = img.mean()\n",
        "print(nighttime_img)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ee.Image({\n",
            "  \"functionInvocationValue\": {\n",
            "    \"functionName\": \"reduce.mean\",\n",
            "    \"arguments\": {\n",
            "      \"collection\": {\n",
            "        \"functionInvocationValue\": {\n",
            "          \"functionName\": \"ImageCollection.load\",\n",
            "          \"arguments\": {\n",
            "            \"id\": {\n",
            "              \"constantValue\": \"NOAA/VIIRS/DNB/MONTHLY_V1/VCMCFG\"\n",
            "            }\n",
            "          }\n",
            "        }\n",
            "      }\n",
            "    }\n",
            "  }\n",
            "})\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LwcT_02UNQOw"
      },
      "source": [
        "u_lon = 4.8148\n",
        "u_lat = 45.7758\n",
        "u_poi = ee.Geometry.Point(u_lon, u_lat)"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ctZPuCLUNTmN"
      },
      "source": [
        "roi = u_poi.buffer(1e6)"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "id": "L_4Y7l9tNCPU",
        "outputId": "85450fee-94d1-40f2-8a7f-d4512178ae14"
      },
      "source": [
        "from IPython.display import Image\n",
        "\n",
        "# Create a URL to the styled image for a region around France.\n",
        "url = nighttime_img.getThumbUrl({\n",
        "    'min': 0, 'max': 60, 'dimensions': 512, 'region': roi})\n",
        "print(url)\n",
        "\n",
        "# Display the thumbnail land surface temperature in France.\n",
        "print('\\nPlease wait while the thumbnail loads, it may take a moment...')\n",
        "Image(url=url)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "error",
          "ename": "EEException",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mHttpError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ee/data.py\u001b[0m in \u001b[0;36m_execute_cloud_call\u001b[0;34m(call, num_retries)\u001b[0m\n\u001b[1;32m    333\u001b[0m   \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 334\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mcall\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnum_retries\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_retries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    335\u001b[0m   \u001b[0;32mexcept\u001b[0m \u001b[0mgoogleapiclient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mHttpError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/googleapiclient/_helpers.py\u001b[0m in \u001b[0;36mpositional_wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    133\u001b[0m                     \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwarning\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 134\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    135\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/googleapiclient/http.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, http, num_retries)\u001b[0m\n\u001b[1;32m    914\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m300\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 915\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mHttpError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muri\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0muri\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    916\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpostproc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontent\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mHttpError\u001b[0m: <HttpError 400 when requesting https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails?fields=name&alt=json returned \"Expression evaluates to an image with inconsistent projections.\". Details: \"Expression evaluates to an image with inconsistent projections.\">",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mEEException\u001b[0m                               Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-17-2556fed7474a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# Create a URL to the styled image for a region around France.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m url = nighttime_img.getThumbUrl({\n\u001b[0;32m----> 5\u001b[0;31m     'min': 0, 'max': 60, 'dimensions': 512, 'region': roi})\n\u001b[0m\u001b[1;32m      6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ee/deprecation.py\u001b[0m in \u001b[0;36mWrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     30\u001b[0m           \u001b[0mfilename\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__code__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mco_filename\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     31\u001b[0m           lineno=func.__code__.co_firstlineno + 1)\n\u001b[0;32m---> 32\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     33\u001b[0m     \u001b[0mdeprecation_message\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'\\nDEPRECATED: '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mmessage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     34\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ee/image.py\u001b[0m in \u001b[0;36mgetThumbURL\u001b[0;34m(self, params)\u001b[0m\n\u001b[1;32m    501\u001b[0m     \u001b[0;31m# If it isn't enabled, we have to be bug-for-bug compatible with current\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    502\u001b[0m     \u001b[0;31m# behaviour.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 503\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmakeThumbUrl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetThumbId\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    504\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    505\u001b[0m   \u001b[0;31m# Deprecated spellings to match the JS library.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ee/image.py\u001b[0m in \u001b[0;36mgetThumbId\u001b[0;34m(self, params)\u001b[0m\n\u001b[1;32m    474\u001b[0m     \u001b[0mimage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mimage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply_visualization\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# pylint: disable=protected-access\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    475\u001b[0m     \u001b[0mparams\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'image'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mimage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 476\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetThumbId\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    477\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    478\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mgetThumbURL\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ee/data.py\u001b[0m in \u001b[0;36mgetThumbId\u001b[0;34m(params, thumbType)\u001b[0m\n\u001b[1;32m    784\u001b[0m     result = _execute_cloud_call(\n\u001b[1;32m    785\u001b[0m         _get_cloud_api_resource().projects().thumbnails().create(\n\u001b[0;32m--> 786\u001b[0;31m             parent=_get_projects_path(), fields='name', body=request))\n\u001b[0m\u001b[1;32m    787\u001b[0m   \u001b[0;32mreturn\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'thumbid'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'name'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'token'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m''\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    788\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/ee/data.py\u001b[0m in \u001b[0;36m_execute_cloud_call\u001b[0;34m(call, num_retries)\u001b[0m\n\u001b[1;32m    334\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mcall\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnum_retries\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_retries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    335\u001b[0m   \u001b[0;32mexcept\u001b[0m \u001b[0mgoogleapiclient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mHttpError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 336\u001b[0;31m     \u001b[0;32mraise\u001b[0m \u001b[0m_translate_cloud_exception\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    337\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    338\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mEEException\u001b[0m: Expression evaluates to an image with inconsistent projections."
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lh3xe9JwNUc6",
        "outputId": "fed96f76-689e-44c7-8e8b-6289cdedbd11"
      },
      "source": [
        "dataset = ee.ImageCollection(\"CIESIN/GPWv411/GPW_Population_Density\").select('population_density')\n",
        "print(dataset)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ee.ImageCollection({\n",
            "  \"functionInvocationValue\": {\n",
            "    \"functionName\": \"Collection.map\",\n",
            "    \"arguments\": {\n",
            "      \"baseAlgorithm\": {\n",
            "        \"functionDefinitionValue\": {\n",
            "          \"argumentNames\": [\n",
            "            \"_MAPPING_VAR_0_0\"\n",
            "          ],\n",
            "          \"body\": {\n",
            "            \"functionInvocationValue\": {\n",
            "              \"functionName\": \"Image.select\",\n",
            "              \"arguments\": {\n",
            "                \"bandSelectors\": {\n",
            "                  \"constantValue\": [\n",
            "                    \"population_density\"\n",
            "                  ]\n",
            "                },\n",
            "                \"input\": {\n",
            "                  \"argumentReference\": \"_MAPPING_VAR_0_0\"\n",
            "                }\n",
            "              }\n",
            "            }\n",
            "          }\n",
            "        }\n",
            "      },\n",
            "      \"collection\": {\n",
            "        \"functionInvocationValue\": {\n",
            "          \"functionName\": \"ImageCollection.load\",\n",
            "          \"arguments\": {\n",
            "            \"id\": {\n",
            "              \"constantValue\": \"CIESIN/GPWv411/GPW_Population_Density\"\n",
            "            }\n",
            "          }\n",
            "        }\n",
            "      }\n",
            "    }\n",
            "  }\n",
            "})\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "egdnfBkJO_aR",
        "outputId": "dbf2d57b-499d-45d0-e247-810fd441cabb"
      },
      "source": [
        "img = dataset.mean()\n",
        "print(img)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ee.Image({\n",
            "  \"functionInvocationValue\": {\n",
            "    \"functionName\": \"reduce.mean\",\n",
            "    \"arguments\": {\n",
            "      \"collection\": {\n",
            "        \"functionInvocationValue\": {\n",
            "          \"functionName\": \"Collection.map\",\n",
            "          \"arguments\": {\n",
            "            \"baseAlgorithm\": {\n",
            "              \"functionDefinitionValue\": {\n",
            "                \"argumentNames\": [\n",
            "                  \"_MAPPING_VAR_0_0\"\n",
            "                ],\n",
            "                \"body\": {\n",
            "                  \"functionInvocationValue\": {\n",
            "                    \"functionName\": \"Image.select\",\n",
            "                    \"arguments\": {\n",
            "                      \"bandSelectors\": {\n",
            "                        \"constantValue\": [\n",
            "                          \"population_density\"\n",
            "                        ]\n",
            "                      },\n",
            "                      \"input\": {\n",
            "                        \"argumentReference\": \"_MAPPING_VAR_0_0\"\n",
            "                      }\n",
            "                    }\n",
            "                  }\n",
            "                }\n",
            "              }\n",
            "            },\n",
            "            \"collection\": {\n",
            "              \"functionInvocationValue\": {\n",
            "                \"functionName\": \"ImageCollection.load\",\n",
            "                \"arguments\": {\n",
            "                  \"id\": {\n",
            "                    \"constantValue\": \"CIESIN/GPWv411/GPW_Population_Density\"\n",
            "                  }\n",
            "                }\n",
            "              }\n",
            "            }\n",
            "          }\n",
            "        }\n",
            "      }\n",
            "    }\n",
            "  }\n",
            "})\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 377
        },
        "id": "pX3Q0WgiOrvX",
        "outputId": "cc6333e2-4468-4507-bbd7-1cba114d7edb"
      },
      "source": [
        "# Import the Image function from the IPython.display module.\n",
        "from IPython.display import Image\n",
        "\n",
        "# Display a thumbnail of global elevation.\n",
        "Image(url = img.updateMask(img.gt(0))\n",
        "  .getThumbURL({'min': 200, 'max': 1000, 'dimensions': 512, 'region': roi,\n",
        "                'palette': [\n",
        "    \"ffffe7\",\n",
        "    \"FFc869\",\n",
        "    \"ffac1d\",\n",
        "    \"e17735\",\n",
        "    \"f2552c\",\n",
        "    \"9f0c21\"\n",
        "  ]}))"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<img src=\"https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/b36bd8d71d97c94d7c84e1a416520eae-4164fed6c71f11b255d4139dbdf26672:getPixels\"/>"
            ],
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 377
        },
        "id": "eloUz_RoO6ui",
        "outputId": "dc887322-682b-4eec-e0ea-2e1770465655"
      },
      "source": [
        "# Get a feature collection of administrative boundaries.\n",
        "countries = ee.FeatureCollection('FAO/GAUL/2015/level0').select('ADM0_NAME')\n",
        "\n",
        "# Filter the feature collection to subset France.\n",
        "france = countries.filter(ee.Filter.eq('ADM0_NAME', 'France'))\n",
        "\n",
        "# Clip the image by France.\n",
        "elv_fr = img.clip(france)\n",
        "\n",
        "# Create the URL associated with the styled image data.\n",
        "url = elv_fr.getThumbUrl({\n",
        "    'min': 200, 'max': 1000, 'region': roi,'dimensions': 512,\n",
        "    'palette': [\"ffffe7\",\n",
        "    \"FFc869\",\n",
        "    \"ffac1d\",\n",
        "    \"e17735\",\n",
        "    \"f2552c\",\n",
        "    \"9f0c21\"]})\n",
        "\n",
        "# Display a thumbnail of elevation in France.\n",
        "Image(url=url)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<img src=\"https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/f032c29921d5ce774ed41f263a1b457b-c7859d5bfcc6e5856c9ff7da6129f09e:getPixels\"/>"
            ],
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mSUIO1CfPbJP"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}